The Development of an Optimized Evaluation System for Improving Coal Dust Suppression Efficiency using Aqueous Solution Sprays


Coal dust has been a serious hazard for the global coal mining industry, and water spray has been commonly used for coal dust suppression. To effectively optimize the dust control efficiency of the aqueous solution, an evaluation system of the solution wettability was investigated and constructed. Different static wetting features (surface tension, contact angle, spreading work, sink time, capillary rise weight and drop penetration time) and dust control efficiency of the solution were studied under different surfactant concentrations. The relationship between static wetting features and an evaluation system was analyzed by the analytic hierarchy process. Additionally, the correlations between static wetting parameters and dust suppression efficiency were investigated. The results indicated that the surfactant concentrations causing the optimal values of different static wetting parameters were inconsistent, and it is not suitable for optimizing the solution wettability based on a single wetting parameter. The weight coefficients of surface tension (0.3265) and sink time (0.2383) on the evaluation system were better than that of other parameters. Additionally, three wetting parameters (surface tension, sink time and spreading work) that have the best correlations with dust control efficiency were used as simple and efficient evaluation indexes to construct the evaluation system. Based on the developed evaluation system, the optimal surfactant concentration was determined.


Mining Engineering


This work was supported by the National Key Research and Development Program of China (2017YFC0805202), the National Natural Science Foundation of China (51774273), Postdoctoral Research Program of Jiangsu Province (2020Z048).

Keywords and Phrases

Coal dust; Dust control efficiency; Dust wettability; Surfactant; Water spray

International Standard Serial Number (ISSN)

0927-7757; 1873-4359

Document Type

Article - Journal

Document Version


File Type





© 2020 Elsevier, All rights reserved.

Publication Date

05 Oct 2020